PRINCIPLES OF ARTIFICIAL NEURAL NETWORKS (2ND EDITION)

PRINCIPLES OF ARTIFICIAL NEURAL NETWORKS (2ND EDITION)

CONTENTS


FRONT MATTER	i
Introduction and Role of Artificial Neural Networks Daniel Graupe	1
Fundamentals of Biological Neural Networks Daniel Graupe	5
Basic Principles of ANNs and Their Early Structures Daniel Graupe	9
The Perceptron Daniel Graupe	17
The Madaline Daniel Graupe	37
Back Propagation Daniel Graupe	59
Hopfield Networks Daniel Graupe	113
Counter Propagation Daniel Graupe	161
Adaptive Resonance Theory Daniel Graupe	179
The Cognitron and the Neocognitron Daniel Graupe	209
Statistical Training Daniel Graupe	215
Recurrent (Time Cycling) Back Propagation Networks Daniel Graupe	233
Large Scale Memory Storage and Retrieval (LAMSTAR) Network Daniel Graupe	249
BACK MATTER	285
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